The simple answer is that you are going to tell a story with data. This is your opportunity to showcase the skills you’ve learned in this course!
Like I mentioned above, each person should spend at least 15 hours on this project. So, the story you tell has to be a bit complex.
I think the most important piece is choosing data or a research question that you are passionate about! Or, to reference Marie Kondo, one that sparks joy.
For example, I love cycling, and I have data on almost all my bike rides for the past 4 or 5 years. Wouldn’t it be cool to tell a story with those data?
I am also passionate about education. I think a lot about how schools are funded. Because I’ve been very involved in fundraising at my kids’ school, I am very curious about how PTO/PTA/etc. influence what types of resources schools are able to have. Listening to the “Nice White Parents” podcast this summer made me even more curious to investigate this. Maybe I could find some data regarding that ….
I am giving you quite a bit of flexibility in what your final project looks like, but I see three larger categories. The one requirement is that it is done completely within R Studio. Assume your audience consists of people that read pop-statistics and pop-computing blogs. You should assume that this audience is not familiar with your project but is comfortable with the fundamentals of data science.
Many articles from The Pudding (one of my favorites compares pocket sizes)
Many articles from ProPublica
Shiny App: type of interactive dashboard that we’ll discuss soon. This option involves less writing but likely requires you to learn a little more coding on your own. In addition to creating the shiny app, you will also be required to submit a “User’s manual” that describes how someone would interact with the app. Check out some examples at the Shiny app gallery, show me shiny gallery, and flexdashboard gallery.
Recorded presesentation: material-wise, similar to the technical blog post, but instead of laying it out like an article, you will create slides and talk about your results.
Title: In the YAML section of the document. A descriptive title & list of all group members.
Introduction and background: An introduction that motivates & outlines a clear, specific set of research questions. Also, provide some background on your topic.
Data collection: Specification of your data sources and collection process.
Analysis: This is the bulk of the report which either has a presentation of the group’s key findings and take-aways or gives the detail of how someone would interact and what people should take away from the shiny app. If you choose to do a shiny app, be sure to include a link to the shinyapps.io site.
Structure & layout: The report follows the above structure and utilizes section/sub-section titles so that readers can easily navigate the report.
Storytelling & cohesion:
Results:
my_really_ugly_variable_name) in your text, visualizations, etc.Code:
echo=FALSE to the options. You may want to wait until after your analysis is complete to include that section because you don’t want to miss those while you’re working on your analysis.gt library functions!Professionalism:
A more detailed description of the project evaluations can be found here (I am still updating this).
Only one member of the group should hand in the final product. This could include knitted html files, videos or links to videos, slides (made in R), etc.
Every member of the group should individually describe what work each group member contributed to the final project in the text input field of their own Moodle assignment. If you or another member of the group contributed substantially more or less work overall, make this clear.